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We examined whether it is possible to estimate the tsunami source model of the 2011 Tohoku-Oki earthquake from a comparison of numerical simulations of tsunami propagation and sediment transport, the measured trace heights, and the sediment thickness of tsunami deposits. Twelve models with different subfault numbers were prepared based on a reference model inferred from tsunami waveform inversion. The reference model with 55 subfaults considering rupture propagation and the model with instantaneous slip successfully reproduced both the tsunami trace heights and sediment thickness distribution of tsunami deposits in the Idagawa Lowland and Sendai Plain. Other models with the same moment magnitude but fewer subfaults could not reproduce the observed trace heights, and the reproducibility of sediment thickness distribution strongly depended on the slip distribution. Models with increased slip amounts and moment magnitude could reproduce the trace heights; however, the simulated sediment thickness was underestimated for the Idagawa Lowland while overestimated for the Sendai Plain. Our results indicate that the combination of trace heights, sediment thickness of tsunami deposits, and numerical simulations of tsunami propagation and sediment transport can be used to estimate historical earthquakes and tsunamis. Efforts should be made to increase the number of subfaults for the study of historical events, although the obtained solutions may not be unique because of fewer trace heights or tsunami deposit data. [ABSTRACT FROM AUTHOR]

High‐frequency (HF) radar monitors the sea surface current velocity and provides information for tsunami early warning. SeaSondeR, an HF ocean radar system in the eastern Tsugaru Strait, Japan, measured the tsunami‐induced current velocity during the 2022 Tonga volcanic tsunami. As an air‐coupled tsunami, the generating mechanism was complex, making it difficult to predict coastal tsunamis using traditional early warning methods. We adopted the tsunami data assimilation (DA) approach, which reconstructs the tsunami wavefield using offshore data and does not require source information, to forecast the coastal tsunami waveforms. Observations from the HF radar and offshore bottom pressure gauges (OBPGs) were used as the input for tsunami DA. The assimilation process started at 09:00 (UTC, hereafter) and forecasts were made at 14:00 and 15:00. The surface current velocity recorded by the HF radar reached the maximum (∼0.25 m/s) at 13:00, which corresponded to a negative phase of ∼2 cm sea level variation observed by OBPGs. We compared the forecasted waveforms with the observed waveforms at Hakodate and Shimokita tide gauges. The assimilation results obtained using HF radar showed a better performance in tsunami forecasting than those using OBPG in this case study. At 14:00, the forecasting accuracy indices were 91% and 67% for the next 2 and 6 hr, respectively. At 15:00, it was 63% and 70% for the next 2 and 6 hr, respectively. We suggest that HF radar could be a good supplement to OBPG for tsunami early warning purposes. Plain Language Summary: On 15 January 2022, the eruption of the Hunga Tonga–Hunga Ha'apai volcano generated a tsunami that arrived in Japan. The tsunami was detected by a high‐frequency (HF) ocean radar system in the eastern Tsugaru Strait. The HF radar recorded the velocity of tsunami‐induced sea surface currents. We used these velocity data to forecast the tsunami waveforms at coastal tide gauge stations. The forecast method, called tsunami data assimilation, does not require tsunami source information but accurately forecasts the coastal tsunami waveforms. We demonstrate that the HF radar data can be successfully applied to tsunami early warning systems. Key Points: High‐frequency (HF) radar observed surface current velocity in the eastern Tsugaru Strait during the 2022 Tonga volcanic tsunamiHF radar observations were used for data assimilation to forecast tsunami waveforms at coastal tide gaugesThe assimilation results using HF radar had an accuracy of over 63% for Hakodate and Shimokita tide gauges [ABSTRACT FROM AUTHOR]

Researchers have developed tsunami inundation models based on nonlinear shallow water equations to estimate tsunami propagation and inundation. However, their empirical results are not in perfect agreement with those of other research institutes, even though the same governing equations are used. Therefore, we quantitatively evaluated the variability of tsunami simulations in this study. Several research institutes have conducted tsunami simulations under the same input conditions using tsunami inundation models adopted for tsunami hazard assessment, resulting in a certain degree of variability among them. By examining the spatial and temporal differences in various physical quantities, we identified the characteristic topography where the variability between tsunami simulations increases. A novel method for calculating statistics from the area integrals of physical quantities was proposed to demonstrate the variability in the overall simulation results. In addition, the effects of different setting parameters and computational environments on the simulation results of a single model were evaluated. The findings of this study are expected to not only serve as a basis to verify the reliability of source codes employed by users of the tsunami inundation model, but also contribute useful technical information to advance probabilistic tsunami hazard assessment in the future. [ABSTRACT FROM AUTHOR]

Tsunami-related fires may occur in the inundation area during a huge tsunami disaster, and woody debris produced by the tsunami can cause the fires to spread. To establish a practical method for evaluating tsunami-related fire predictions, we previously developed a method for evaluating the tsunami debris thickness distribution that uses tsunami computation results and static parameters for tsunami numerical analysis. We then used this evaluation method to successfully reproduce the tsunami debris accumulation trend. We then developed an empirical building fragility function that relates the production of debris not only to inundation depth but also to the topographic gradient and the proportion of robust buildings. Using these empirical evaluation models, along with conventional tsunami numerical analysis data, we carried out a practical tsunami debris prediction for Owase City, Mie Prefecture, a potential disaster area for a Nankai Trough mega-earthquake. This prediction analysis method can reveal hazards which go undetected by a conventional tsunami inundation analysis. These results indicate that it is insufficient to characterize the tsunami hazard by inundation area and inundation depth alone when predicting the hazard of a huge tsunami; moreover, more practically, it is necessary to predict the hazard based on the effect of tsunami debris. [ABSTRACT FROM AUTHOR]

We estimated the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai earthquakes from tidal records of two tide gauge stations (San Francisco and San Diego) on the west coast of North America. The first signals of the Ansei–Tokai tsunami were apparent, whereas those of the Ansei–Nankai tsunami were obscured by the later waves of the Ansei–Tokai tsunami. Waveforms of the Ansei–Nankai tsunami simulated with nonlinear dispersive wave theory by assuming an origin time of 07:00 GMT on 24 December arrived earlier than in the observations. The normalized root mean square and the misfit between the simulated and observed waveforms of the Ansei–Nankai tsunami showed a time difference between them of approximately 0.4 h. This finding suggests that the actual origin time of the Ansei–Nankai tsunami was approximately 07:24 GMT on 24 December. A previous study estimated the origin time of the Ansei–Tokai tsunami to be about 00:30 GMT on 23 December. Thus, we concluded that the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai tsunamis was 30.9 h. Despite the significant difference in the time resolution between the seasonal timekeeping system used in Japan in 1854 and waveform digitization, our result is roughly in agreement with historical descriptions of the tsunamis, suggesting that such information can be effectively used to determine the origin times of historical earthquakes. [ABSTRACT FROM AUTHOR]

Although tsunamis are dispersive water waves, hazard maps for earthquake-generated tsunamis neglect dispersive effects because the spatial dimensions of tsunamis are much greater than the water depth, and dispersive effects are generally small. Furthermore, calculations that include non-dispersive effects tend to predict higher tsunamis than ones that include dispersive effects. Although non-dispersive models may overestimate the tsunami height, this conservative approach is acceptable in disaster management, where the goal is to save lives and protect property. However, we demonstrate that offshore frequency dispersion amplifies tsunamis caused by outer-rise earthquakes, which displace the ocean bottom downward in a narrow area, generating a dispersive short-wavelength and pulling-dominant (water withdrawn) tsunami. We compared observational evidence and calculations of tsunami for a 1933 Mw 8.3 outer-rise earthquake along the Japan Trench. Dispersive (Boussinesq) calculations predicted significant frequency dispersion in the 1933 tsunami. The dispersive tsunami deformation offshore produced tsunami inundation heights that were about 10% larger than those predicted by non-dispersive (long-wave) calculations. The dispersive tsunami calculations simulated the observed tsunami inundation heights better than did the non-dispersive tsunami calculations. Contrary to conventional practice, we conclude that dispersive calculations are essential when preparing deterministic hazard maps for outer-rise tsunamis. [ABSTRACT FROM AUTHOR]